3 papers
cs.DC2026
Bidirectional Resource Scheduling for Disaggregated and Asynchronous RL Post-Training
Tan Zhiqiang, Zhiqiang Tan, Maoxin Wang +11
It is well established that the reasoning capabilities of large language models (LLMs) can be improved by applying reinforcement learning (RL) in a post-training stage. In a standa…
cs.AI2026
Accelerating Disaggregated RL for Visual Generative LLMs with Diffusion-Based Parallelism and Trainer-Assisted Generation
Sijie Wang, Zhengyu Qing, Zhiqiang Tan +6
Reinforcement learning (RL) has become a dominant post-training paradigm, driving the emergence of high-performance RL systems such as veRL for autoregressive large language models…
cs.CV2025
PipeDiT: Accelerating Diffusion Transformers in Video Generation with Task Pipelining and Model Decoupling
Sijie Wang, Qiang Wang, Shaohuai Shi
Video generation has been advancing rapidly, and diffusion transformer (DiT) based models have demonstrated remark- able capabilities. However, their practical deployment is of- te…